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Record W4293228519 · doi:10.1080/14459795.2022.2041067

A scoping review of experimental manipulations examining the impact of monetary format on gambling behaviour

2022· review· en· W4293228519 on OpenAlexafffund
Lucas Palmer, Natalie Cringle, Luke Clark

Bibliographic record

VenueInternational Gambling Studies · 2022
Typereview
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsPaymentSalience (neuroscience)CashContext (archaeology)Payment cardTicketEconomicsBusinessPsychologyComputer scienceFinanceComputer securityCognitive psychology

Abstract

fetched live from OpenAlex

Gambling involves monetary bets and prizes, but the money can take a range of formats, including cash, chips, ticket-in ticket-out vouchers, and digital options including banking cards. As societies move toward cashless payment for many goods, the question arises of how emerging payment technologies might impact gambling-related harms. We performed a scoping review following PRISMA guidelines to identify research testing the effects of monetary format in gambling. Our eligibility criteria focused on controlled experimental manipulations, to best establish the causal impact of monetary format. We sought to characterize different types of monetary manipulations that have been studied in a gambling context. We identified 19 eligible articles, comprising 23 individual experiments. These experiments were organized according to four distinct manipulations. The most common design (12 experiments), compared gambling under the presence or absence of money. Smaller numbers of experiments were identified manipulating monetary salience, testing Responsible Gambling tools, and testing the impact of promotional inducements. We identified no studies that compared gambling using cash against digital payment forms. Our review highlights a paucity of research testing the possible impact of digital and cashless payment options on gambling related harms, using experimental designs that would permit causal conclusions to be drawn.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.560
GPT teacher head0.587
Teacher spread0.027 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes2
Has abstractyes

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